Professor and associate member of MILA, the Montreal Institute for Learning Algorithms, Allan Tapp, is a long-time researcher in physics, computer science, and mathematics. From his early studies in these fields, he now brings his expertise to artificial intelligence and deep learning.

The MILA is an institute which began with the main ambition on the study of machine learning and learning of algorithms. Tapp realized the importance of artificial intelligence and took the opportunity to move into this field and is now fully committed to the technology through his continuing research at MILA.

Tapp sits down with us to explain how the different types of AI machine learning work, the advancements in the field and he also discusses some common doomsday scenarios. Although he feels it is important that people are concerned about what machine learning means for man kind’s future, he clarifies of the unlikelihood of such occurrences based on the level of technology we are at today.

In this interview, Tapp also touches on the possible future of AI and deep learning. He describes what he thinks is on the horizon, specifically his interests in the concept of memory based neural networks and better Q & A dialogue with machines.